问题描述
我用过这个博客的代码“https://learnopencv.com/deep-learning-based-object-detection-and-instance-segmentation-using-mask-r-cnn-in-opencv-python-c /" 题为在 Python 中使用 OpenCV 中的 Mask R-CNN 进行基于深度学习的对象检测和实例分割。我正在使用实时流并希望对其进行对象检测和实例分割,并修改了下面的代码,其余代码与博客中的解释相同
input_path = 'rtsp://...'
cap = cv.VideoCapture(input_path)
print(cap.isOpened())
# We need to set resolutions.
# so,convert them from float to integer.
frame_width = int(cap.get(3))
frame_height = int(cap.get(4))
size = (frame_width,frame_height)
#cv2.VideoWriter( filename,fourcc,fps,frameSize )
result = cv.VideoWriter('sample.avi',cv.VideoWriter_fourcc(*'MJPG'),22,size),round(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
while True:
ret,frame = cap.read()
if ret:
# You can do processing on this frame variable
blob = cv.dnn.blobFromImage(frame,swapRB=True,crop=False)
# Set the input to the network
net.setInput(blob)
# Run the forward pass to get output from the output layers
Boxes,masks = net.forward(['detection_out_final','detection_masks'])
# Extract the bounding Box and mask for each of the detected objects
postprocess(Boxes,masks)
# Put efficiency @R_57_4045@ion.
t,_ = net.getPerfProfile()
label = 'Mask-RCNN : Inference time: %.2f ms' % (t * 1000.0 / cv.getTickFrequency())
cv.putText(frame,label,(0,15),cv.FONT_HERShey_SIMPLEX,0.5,0))
result.write(frame.astype(np.uint8))
cv.imshow("winName",frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
result.release()
cap.release()
cv.destroyAllWindows()
运行此程序时出现以下错误
AttributeError Traceback (most recent call last)
<ipython-input-10-9712242a2634> in <module>
36 cv.putText(frame,0))
37
---> 38 result.write(frame)
39
40 cv.imshow("winName",frame)
AttributeError: 'tuple' object has no attribute 'write'
如何纠正这个错误。
解决方法
Result
是一个长度为 2 的元组,而它应该是一个简单的类型,您可以将第 38 行更改为:
result[0].write(frame.astype(np.uint8))
值 python round(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
似乎没有做任何事情,因此您可以通过将第 12-14 行替换为:
result = cv.VideoWriter('sample.avi',cv.VideoWriter_fourcc(*'MJPG'),22,size)
,
在这一行中,您正在创建一个元组
result = cv.VideoWriter('sample.avi',size),round(cap.get(cv.CAP_PROP_FRAME_HEIGHT))
简单地做
result = cv.VideoWriter('sample.avi',size)
variableX = round(cap.get(cv.CAP_PROP_FRAME_HEIGHT))